Instructions to use keshavkmr076/email-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keshavkmr076/email-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keshavkmr076/email-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("keshavkmr076/email-classification") model = AutoModelForSequenceClassification.from_pretrained("keshavkmr076/email-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (b9631cad82a44b92db4bad281dab5906ae0ddcca) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>5397796
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adding all artefacts of model for email classification : email nature
98816c1 -
initial commit
265f1a1